class_docstr: Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
code: def __init__(
      self, in_features, out_features, dropout=0.0, act=F.relu
  ):
      super(GraphConvolution, self).__init__()
      self.in_features = in_features
      self.out_features = out_features
      self.dropout = dropout
      self.act = act
      self.weight = Parameter(
          torch.FloatTensor(in_features, out_features)
      )
      self.reset_parameters()
  
file_path: graph4nlp/graph4nlp/pytorch/test/link_prediction/layers.py
imports: import torch
  import torch.nn.functional
  from torch.nn.modules.module import Module
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 1 to create a new GraphConvolution object from inherited base classes: Module with example: obj = GraphConvolution(in_features, out_features, dropout, act)